code: def ssd_300_vgg16_atrous_coco(
      pretrained=False, pretrained_base=True, **kwargs
  ):
      """SSD architecture with VGG16 atrous 300x300 base network for COCO.
  
      Parameters
      ----------
      pretrained : bool or str
          Boolean value controls whether to load the default pretrained weights for model.
          String value represents the hashtag for a certain version of pretrained weights.
      pretrained_base : bool or str, optional, default is True
          Load pretrained base network, the extra layers are randomized.
  
      Returns
      -------
      HybridBlock
          A SSD detection network.
      """
      from ...data import COCODetection
  
      classes = COCODetection.CLASSES
      net = get_ssd(
          "vgg16_atrous",
          300,
          features=vgg16_atrous_300,
          filters=None,
          sizes=[21, 45, 99, 153, 207, 261, 315],
          ratios=[[1, 2, 0.5]]
          + [[1, 2, 0.5, 3, 1.0 / 3]] * 3
          + [[1, 2, 0.5]] * 2,
          steps=[8, 16, 32, 64, 100, 300],
          classes=classes,
          dataset="coco",
          pretrained=pretrained,
          pretrained_base=pretrained_base,
          **kwargs,
      )
      return net
  
imports: from __future__ import absolute_import
  import warnings
  from gluoncv.data import VOCDetection
  from .ssd import get_ssd
  from ..ssd.anchor import LiteAnchorGenerator
  from ..ssd.vgg_atrous import vgg16_atrous_300, vgg16_atrous_512
label_desc: Use image node_id 2 for calling a global function with example usage: ssd_300_vgg16_atrous_coco(pretrained, pretrained_base) and returns: net